Characterizing the Self-Potential Response to Concentration Gradients in Heterogeneous Subsurface Environments
Characterizing the Self-Potential Response to Concentration Gradients in Heterogeneous Subsurface Environments
复制标题
表征非均质地下环境中浓度梯度的自势响应
DOI：
10.1029/2019jb017829
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发表时间：
2019
期刊：
影响因子：
3.4
通讯作者：
MacAllister D
中科院分区：
文献类型：
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作者：
MacAllister D
自然电位（SP）测量可用于真实的实时表征和监测地下流体的运动和行为。当多孔介质中存在浓度梯度时，电化学排阻扩散（EED）电位（SP的一个组成部分）出现。这种浓度梯度在沿海和受污染的含水层以及石油和天然气储藏中令人关切。在具有异质地质和盐度对比的复杂环境中进行SP调查之前，必须对EED潜力进行估计，例如英国Chalk沿海含水层。在这里，我们报告可重复的实验室估计的EED潜力的白垩和泥灰岩使用天然地下水（GW），海水（SW），去离子（DI）水，和5 M NaCl。在所有情况下，白垩的EED电位都是正的（使用GW/SW浓度梯度，EED电位约为1.5%）。14至22 mV），在较高的盐度对比度下，与扩散极限的偏差增加。尽管白垩的孔隙尺寸相对较小（约。1 μm），它是由扩散势占主导地位，并具有低的排斥效率，即使在大的盐度对比。泥灰岩样品具有更高的排阻效率，其具有足以逆转EED电位的极性的量值（使用GW/SW浓度梯度，EED电位为约1.5。-7至-12 mV）。尽管使用的天然样品很复杂，但该方法产生了可重复的结果。我们还表明，可以使用SP日志进行排除效率的一阶估计，支持Graham等人（2018，https：//doi.org/10.1029/2018WR022972）中报告的模型的参数化，并且泥灰岩的推导值与实验室实验一致，而基于现场数据的硬地推导值表明类似的高排除效率。虽然这种方法在没有实验室测量的情况下显示出希望，但在可能的情况下应进行更严格的估计，并可按照本文报告的实验方法进行。
Self‐potential (SP) measurements can be used to characterize and monitor, in real‐time, fluid movement and behavior in the subsurface. The electrochemical exclusion‐diffusion (EED) potential, one component of SP, arises when concentration gradients exist in porous media. Such concentration gradients are of concern in coastal and contaminated aquifers and oil and gas reservoirs. It is essential that estimates of EED potential are made prior to conducting SP investigations in complex environments with heterogeneous geology and salinity contrasts, such as the UK Chalk coastal aquifer. Here we report repeatable laboratory estimates of the EED potential of chalk and marls using natural groundwater (GW), seawater (SW), deionized (DI) water, and 5 M NaCl. In all cases, the EED potential of chalk was positive (using a GW/SW concentration gradient the EED potential was ca. 14 to 22 mV), with an increased deviation from the diffusion limit at the higher salinity contrast. Despite the relatively small pore size of chalk (ca. 1 μm), it is dominated by the diffusion potential and has a low exclusion efficiency, even at large salinity contrasts. Marl samples have a higher exclusion efficiency which is of sufficient magnitude to reverse the polarity of the EED potential (using a GW/SW concentration gradient the EED potential was ca. −7 to −12 mV) with respect to the chalk samples. Despite the complexity of the natural samples used, the method produced repeatable results. We also show that first order estimates of the exclusion efficiency can be made using SP logs, supporting the parameterization of the model reported in Graham et al. (2018, https://doi.org/10.1029/2018WR022972), and that derived values for marls are consistent with the laboratory experiments, while values derived for hardgrounds based on field data indicate a similarly high exclusion efficiency. While this method shows promise in the absence of laboratory measurements, more rigorous estimates should be made where possible and can be conducted following the experimental methodology reported here.